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@ccamel
ccamel / README.md
Last active July 23, 2026 20:23
🐑 An opinionated HerdR launcher for how I currently do multi-agent dev in Git repos

A small, opinionated HerdR launcher for my current workflow.

The idea is simple: from any Git repository, run herd and spawn a ready-to-use HerdR workspace with one agent tab powered by omp.sh, plus editor, runner, terminal and git tabs.

The tabs look like this:

🤖 agent | 📝 editor | 🌿 changes | 🔀 diff | 🏃 run | 🖥️ term
@wojteklu
wojteklu / clean_code.md
Last active July 23, 2026 20:14
Summary of 'Clean code' by Robert C. Martin

Code is clean if it can be understood easily – by everyone on the team. Clean code can be read and enhanced by a developer other than its original author. With understandability comes readability, changeability, extensibility and maintainability.


General rules

  1. Follow standard conventions.
  2. Keep it simple stupid. Simpler is always better. Reduce complexity as much as possible.
  3. Boy scout rule. Leave the campground cleaner than you found it.
  4. Always find root cause. Always look for the root cause of a problem.

Design rules

@ironlungx
ironlungx / nvim-pio.md
Last active July 23, 2026 20:10
PlatformIO with Neovim

Caution

I've moved this gist over to a template repository here. Everything here is unmaintained...

Extensions

Following are the extensions required for neovim:

@cseeman
cseeman / markdown_examples.md
Last active July 23, 2026 20:08
Markdown for info panel/warning box

Examples for how to create your own info panel, warning box and other decent looking notification in GitHub markdown.

All the boxes are single/two cell tables or two row tables.

Warning box

❗ You have to read about this
@rdebath
rdebath / README
Last active July 23, 2026 20:07
Original brainfuck distribution by Urban Müller
This archive contains the following programs:
bfc The compiler for the 'brainfuck' language (240 bytes!)
bfc.asm Source for the compiler
bfi The interpreter for the 'brainfuck' language
bfi.c Source for the interpreter (portable)
src/ Some example programs in 'brainfuck'
src/atoi.b Reads a number from stdin
src/div10.b Divides the number under the pointer by 10
src/hello.b The ubiquitous "Hello World!"
@sgup
sgup / recommended-routine.md
Last active July 23, 2026 20:06
Recommended Routine - Reddit BodyweightFitness
@WildSiphon
WildSiphon / DockerDesktop.yaml
Created July 5, 2025 11:00
Docker Desktop direct download links
4.0.0:
Windows: https://desktop.docker.com/win/main/amd64/67817/Docker%20Desktop%20Installer.exe
Mac with Intel chip: https://desktop.docker.com/mac/main/amd64/67817/Docker.dmg
Mac with Apple chip: https://desktop.docker.com/mac/main/arm64/67817/Docker.dmg
release_date: '2021-08-31'
4.0.1:
Windows: https://desktop.docker.com/win/main/amd64/68347/Docker%20Desktop%20Installer.exe
Mac with Intel chip: https://desktop.docker.com/mac/main/amd64/68347/Docker.dmg
Mac with Apple chip: https://desktop.docker.com/mac/main/arm64/68347/Docker.dmg
release_date: '2021-09-13'
@mondain
mondain / public-stun-list.txt
Last active July 23, 2026 20:04
Public STUN server list
23.21.150.121:3478
iphone-stun.strato-iphone.de:3478
numb.viagenie.ca:3478
s1.taraba.net:3478
s2.taraba.net:3478
stun.12connect.com:3478
stun.12voip.com:3478
stun.1und1.de:3478
stun.2talk.co.nz:3478
stun.2talk.com:3478
@borgar
borgar / .block
Last active July 23, 2026 20:01
PRS B1919+21
license: cc-by-nc-sa-4.0
height: 500
border: no

LLM Wiki

A pattern for building personal knowledge bases using LLMs.

This is an idea file, it is designed to be copy pasted to your own LLM Agent (e.g. OpenAI Codex, Claude Code, OpenCode / Pi, or etc.). Its goal is to communicate the high level idea, but your agent will build out the specifics in collaboration with you.

The core idea

Most people's experience with LLMs and documents looks like RAG: you upload a collection of files, the LLM retrieves relevant chunks at query time, and generates an answer. This works, but the LLM is rediscovering knowledge from scratch on every question. There's no accumulation. Ask a subtle question that requires synthesizing five documents, and the LLM has to find and piece together the relevant fragments every time. Nothing is built up. NotebookLM, ChatGPT file uploads, and most RAG systems work this way.